Construction of a Multidimensional Dynamic Early Warning System for Genetic-Immune-Inflammatory Disorders in Precision Prevention and Control of Neonatal Necrotizing Enterocolitis: A Multicenter Clinical Study

Necrotizing enterocolitis (NEC) is one of the most severe gastrointestinal emergencies in preterm infants, characterized by insidious onset, rapid progression, and high mortality. It can lead to serious adverse outcomes such as intestinal perforation, short bowel syndrome, and neurodevelopmental disorders, making it a critical condition that significantly impacts the survival quality and long-term prognosis of preterm infants.With the advancement of perinatal medicine in China, the survival rates of extremely low and very low birth weight infants have been continuously improving. NEC has become a critical bottleneck constraining the quality of care and long-term prognosis for preterm infants.

Previous studies have demonstrated that various perinatal and early postnatal factors, including gestational age, birth weight, infection, feeding methods, blood transfusion, mechanical ventilation, and antibiotic exposure, are associated with the occurrence of NEC. However, these clinical factors still fail to adequately explain the interindividual variations in NEC incidence risk and disease severity under similar clinical exposure conditions.Existing NEC prediction models primarily rely on static baseline variables for one-time risk assessment, lacking dynamic risk updates during hospitalization, and most are derived from single-center retrospective studies.

With the application of clinical exome sequencing (CES), the role of genetic factors in susceptibility to NEC has gradually attracted attention.The research team has previously conducted NEC risk gene screening based on CES, genetic burden analysis, and exploration of genetic-clinical factor interactions, suggesting that genetic information can provide important supplementation for NEC risk assessment.Meanwhile, dynamic changes in immune-inflammatory markers such as peripheral blood eosinophils, NLR, absolute neutrophil count, and platelet count may already exhibit abnormalities prior to the onset of NEC, providing repeatable, low-cost, and clinically available signals for early identification.Based on this, this study aims to establish a multidimensional dynamic early warning system for NEC integrating single-center preliminary genetic research foundations with multi-center retrospective/prospective validation resources. This initiative seeks to enhance the identification capability of high-risk individuals and provide evidence for subsequent precision prevention and control as well as stratified management.